docs: def extract(filename_url_filelike_or_htmlstring):
      """An "improved" algorithm over the original eatiht algorithm
      """
      html_tree = get_html_tree(filename_url_filelike_or_htmlstring)
  
      subtrees = get_textnode_subtrees(html_tree)
      #[iterable, cardinality, ttl across iterable, avg across iterable.])
  
      # calculate AABSL
      avg, _, _ = calcavg_avgstrlen_subtrees(subtrees)
  
      # "high-pass" filter
      filtered = [subtree for subtree in subtrees
                  if subtree.ttl_strlen > avg]
  
      paths = [subtree.parent_path for subtree in filtered]
  
      hist = get_xpath_frequencydistribution(paths)
  
      target_subtrees = [stree for stree in subtrees
                         if hist[0][0] in stree.parent_path]
  
      title = html_tree.find(".//title")
  
      return TextNodeTree(title.text_content(), target_subtrees, hist)